Remote Sensing Methods for the Retrieval of Inventory and Bioproductivity Parameters of Forests Using High Resolution Satellite Images

Remote Sensing Methods for the Retrieval of Inventory and Bioproductivity Parameters of Forests Using High Resolution Satellite Images

A method for automated processing high spatial resolution satellite images is proposed to retrieve inventory and bioproductivity parameters of forest stands. The method includes effective learning classifiers, inverse modeling, and regression modeling of the estimated parameters. Spectral and textur...

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Main Authors: Dmitriev Egor, Kozoderov Vladimir, Donskoy Sergey, Melnik Petr, Sokolov Anton
Format: Article
Language:English
Published: EDP Sciences 2019-01-01
Series:E3S Web of Conferences
Online Access:https://doi.org/10.1051/e3sconf/20197501003
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spelling doaj-2b0411680718435e921695422705c2432021-02-02T04:11:47ZengEDP SciencesE3S Web of Conferences2267-12422019-01-01750100310.1051/e3sconf/20197501003e3sconf_rpers2018_01003Remote Sensing Methods for the Retrieval of Inventory and Bioproductivity Parameters of Forests Using High Resolution Satellite ImagesDmitriev EgorKozoderov VladimirDonskoy SergeyMelnik PetrSokolov AntonA method for automated processing high spatial resolution satellite images is proposed to retrieve inventory and bioproductivity parameters of forest stands. The method includes effective learning classifiers, inverse modeling, and regression modeling of the estimated parameters. Spectral and texture features are used to classify forest species. The results of test experiments for the selected area of Savvatievskoe forestry (Russia, Tver region) are presented. Accuracy estimates obtained using ground-based measurements demonstrate the effectiveness of using the proposed techniques to automate the process of updating information for the State Forest Inventory program of Russia.https://doi.org/10.1051/e3sconf/20197501003
collection DOAJ
language English
format Article
sources DOAJ
author Dmitriev Egor
Kozoderov Vladimir
Donskoy Sergey
Melnik Petr
Sokolov Anton
spellingShingle Dmitriev Egor
Kozoderov Vladimir
Donskoy Sergey
Melnik Petr
Sokolov Anton
Remote Sensing Methods for the Retrieval of Inventory and Bioproductivity Parameters of Forests Using High Resolution Satellite Images
E3S Web of Conferences
author_facet Dmitriev Egor
Kozoderov Vladimir
Donskoy Sergey
Melnik Petr
Sokolov Anton
author_sort Dmitriev Egor
title Remote Sensing Methods for the Retrieval of Inventory and Bioproductivity Parameters of Forests Using High Resolution Satellite Images
title_short Remote Sensing Methods for the Retrieval of Inventory and Bioproductivity Parameters of Forests Using High Resolution Satellite Images
title_full Remote Sensing Methods for the Retrieval of Inventory and Bioproductivity Parameters of Forests Using High Resolution Satellite Images
title_fullStr Remote Sensing Methods for the Retrieval of Inventory and Bioproductivity Parameters of Forests Using High Resolution Satellite Images
title_full_unstemmed Remote Sensing Methods for the Retrieval of Inventory and Bioproductivity Parameters of Forests Using High Resolution Satellite Images
title_sort remote sensing methods for the retrieval of inventory and bioproductivity parameters of forests using high resolution satellite images
publisher EDP Sciences
series E3S Web of Conferences
issn 2267-1242
publishDate 2019-01-01
description A method for automated processing high spatial resolution satellite images is proposed to retrieve inventory and bioproductivity parameters of forest stands. The method includes effective learning classifiers, inverse modeling, and regression modeling of the estimated parameters. Spectral and texture features are used to classify forest species. The results of test experiments for the selected area of Savvatievskoe forestry (Russia, Tver region) are presented. Accuracy estimates obtained using ground-based measurements demonstrate the effectiveness of using the proposed techniques to automate the process of updating information for the State Forest Inventory program of Russia.
url https://doi.org/10.1051/e3sconf/20197501003
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AT kozoderovvladimir remotesensingmethodsfortheretrievalofinventoryandbioproductivityparametersofforestsusinghighresolutionsatelliteimages
AT donskoysergey remotesensingmethodsfortheretrievalofinventoryandbioproductivityparametersofforestsusinghighresolutionsatelliteimages
AT melnikpetr remotesensingmethodsfortheretrievalofinventoryandbioproductivityparametersofforestsusinghighresolutionsatelliteimages
AT sokolovanton remotesensingmethodsfortheretrievalofinventoryandbioproductivityparametersofforestsusinghighresolutionsatelliteimages
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